Scalable Cytometry Image Processing (SCIP) is an open-source tool that implements an image processing pipeline on top of Dask, a distributed computing framework written in Python. SCIP performs projection, illumination correction, image segmentation and masking, and feature extraction.
Principal feature analysis is a method for selecting the features which describe most variance in a dataset. It is based on PCA.
Blog post explaining PFA: https://biapol.github.io/blog/ryan_savill/principal_feature_analysis/ PFA paper: http://venom.cs.utsa.edu/dmz/techrep/2007/CS-TR-2007-011.pdf